Studies in Educational Evaluation 47 (2015) 19–27
Contents lists available at ScienceDirect
Studies in Educational Evaluation journal homepage: www.elsevier.com/stueduc
Exposing biology teachers’ tacit views about the knowledge that is required for teaching using the repertory grid technique Ronit Rozenszajn, Anat Yarden * Department of Science Teaching, Weizmann Institute of Science, Rehovot 76100, Israel
A R T I C L E I N F O
A B S T R A C T
Article history: Received 1 April 2015 Received in revised form 29 May 2015 Accepted 2 June 2015 Available online
Several types of knowledge are known to be required for teaching, including content knowledge (CK) and pedagogical content knowledge (PCK). Exploring the relationships between CK and PCK is not a straightforward task due to their complex and tacit nature. Here we aim to expose biology teachers’ views about the knowledge required for teaching biology and their tacit views about the relationships between CK and PCK using the repertory grid technique. Data collected from 23 in-service experienced high-school biology teachers revealed that CK is viewed by the participating teachers as an important component of knowledge for teaching. Analysis of their tacit views about the relationships between CK and PCK revealed that CK is viewed by and large as distinct from PCK. ß 2015 Elsevier Ltd. All rights reserved.
Keywords: Biology teacher Content knowledge Pedagogical content knowledge Personal construct psychology theory Repertory grid technique Tacit view
1. Rational Experienced teachers possess special knowledge, acquired during their teaching. Considerable effort has been made in the last three decades to construct a well-established conception of science teachers’ knowledge. It was Shulman (1986) who first suggested that there are several types of knowledge required for teaching, including content knowledge (CK) and pedagogical content knowledge (PCK). Shulman defined CK as the amount and organization of subject-matter knowledge per se in the teacher’s mind, and PCK as a unique amalgam of content and pedagogical knowledge that reflects the ways in which the subject is presented and formulated to make it comprehensible to others (Shulman, 1986, 1987). Both CK and PCK are considered critical professional development resources for teachers, each requiring special attention during teacher training and classroom teaching practice (Baumert et al., 2010). While many scholars agree with Shulman’s (1986) categorization of science teachers’ knowledge which distinguishes CK from PCK (Grossman, 1990; Krauss et al., 2008; Lederman & Gess-Newsome, 1992; Magnusson, Krajcik, & Borko, 1999), others
* Corresponding author. Tel.: +972 8 9344044; fax: +972 8 9342681. E-mail addresses:
[email protected] (R. Rozenszajn),
[email protected] (A. Yarden). http://dx.doi.org/10.1016/j.stueduc.2015.06.001 0191-491X/ß 2015 Elsevier Ltd. All rights reserved.
refer to CK as an integral part of PCK (Ball, Thames, & Phelps, 2008; Hill, 2008; Lee & Luft, 2008; Marks, 1990). Various methods have been developed to measure the knowledge required for teaching. These include meta-analysis (Zeidler, 2002), interviews, and multiple-choice and open-ended questionnaires about teaching and learning situations (Baumert et al., 2010; Hill, 2008; Ka¨pyla¨, Heikkinen, & Asunta, 2009), as well as classroom observation (Rozenszajn & Yarden, 2011, 2014a). CK may be easier to expose, because of its explicit nature, than PCK, which is largely tacit. Moreover, the relationships between CK and PCK are largely tacit, complicating their examination due to their complex nature and internal tacit construct (Loughran, Milroy, Berry, Gunstone, & Mulhall, 2001), as well as their dependence on context (Driel, Verloop, & De Vos, 1998). Indeed, in-service teachers who develop expertise in teaching hold tacit or intuitive knowledge—the experts know what they should do while teaching, but cannot necessarily explain why it is done (Bjo¨rklund, 2008). The exploration of explicit knowledge may therefore reveal only part of the teachers’ knowledge, calling for the need to elicit teachers’ implicit knowledge and their views about this knowledge to obtain a full picture. Here we used the repertory grid technique (RGT), which has been previously used to elicit experts’ personal views (Fransella, Bell, & Bannister, 2004; Jankowicz, 2001). This study focused on high-school biology teachers who were participating in a longterm professional development program that was specifically
20
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
designed for outstanding science teachers (see research context below). The goals of this study were to expose in-service biology teachers’ views about the knowledge required for teaching biology in general and their tacit views about the relationships between CK and PCK in particular, using the RGT.
2. Theoretical framework 2.1. Teachers’ knowledge base Teachers hold a large and unique teaching knowledge. It was Shulman (1986) who first suggested referring to teachers’ knowledge as a special knowledge domain. He divided this special knowledge into three categories: (a) subject matter CK—the amount and organization of knowledge per se in the teacher’s mind; (b) PCK—the dimension of subject matter for teaching, namely the ways of presenting and formulating the subject to make it comprehensible to others, and (c) curricular knowledge— the knowledge of alternative curriculum materials for a given subject or topic within a grade (Shulman, 1986). Shulman’s PCK model was further discussed and revised by various science educators, suggesting more detailed representations. Grossman (1990) proposed a model that provides four categories of PCK: conceptions of purposes for teaching a particular subject matter, knowledge of student understanding, curricular knowledge, and knowledge of instructional strategies. Magnusson et al. (1999) changed Grossman’s use of the term ‘purposes’ to ‘orientation’, added beliefs to knowledge, and added an additional category: knowledge and beliefs about assessment. Since then, major effort has been devoted to understanding the notion of PCK and constructing a well-established conception for PCK and its related categories (Gess-Newsome, 1999; Lee & Luft, 2008; Park & Oliver, 2008; Rozenszajn & Yarden, 2011, 2014a, 2014b). By and large, it is agreed that PCK is used in the context of teaching a specific content (Ball et al., 2008; De Jong & Van Der Valk, 2007; Lee & Luft, 2008; Loughran et al., 2001; Loughran, Mulhall, & Berry, 2008; Magnusson et al., 1999), but resolution of the term ‘‘specific content’’ is still under debate. While some researchers refer to the term ‘‘content’’ of the construct PCK as the knowledge of teaching a specific subject matter (De Jong & Van Der Valk, 2007; Henze, Van Driel, & Verloop, 2008; Loughran et al., 2008; Rozenszajn & Yarden, 2014a; Van Driel et al., 1998), others refer to it as ‘‘the knowledge of teaching all the topics they teach’’ (Magnusson et al., 1999; Shulman, 1987). In addition to the need to understand PCK, the relationships between PCK components and CK as an integral part of teachers’ knowledge for practice have been discussed. Some researchers suggest that CK enhances teachers’ quality of teaching. For example, in mathematics education, the breadth, depth, and flexibility of teachers’ understanding of the mathematics they teach afford them a broader and more varied repertoire of teaching strategies (Ball et al., 2008; Baumert et al., 2010; Even, 2011; Krauss et al., 2008), while limited CK has been shown to be detrimental to PCK, limiting the scope of its development (Baumert et al., 2010). Moreover, it has been suggested that the degree of cognitive connectedness between CK and PCK among secondary mathematics teachers is a function of their degree of mathematical expertise (Krauss et al., 2008). In contrast, other studies have indicated that science teachers’ subject-matter knowledge is not automatically transferred to classroom practice (Lederman & GessNewsome, 1992; Zeidler, 2002), implying that CK and PCK are different and distinct domains within the teacher’s cognitive structures (Grossman, 1990; Großschedla, Mahlera, Kleickmann, & Harmsa, 2014; Magnusson et al., 1999; Shulman, 1986). Examining the relationships between CK and PCK is complicated because
expert teachers hold tacit knowledge about the role of PCK in their practice (Bjo¨rklund, 2008) which is not easily revealed. 2.2. Tacit knowledge and the personal construct psychology theory Tacit knowledge is contextual and situated. It is often acquired through repeated experiences with a certain domain. Experts in a field are those who repeatedly have certain experiences and effectively learn from them. Therefore, they are usually able to recognize meaningful patterns faster than novices (Chi, 2006; Dreyfus, 2004), but they will be unable to verbalize this and will often be unaware of it (Polanyi, 1966). Namely, experts facing an unfamiliar situation will intuitively identify what should be done: they do not even seem to think about it. They just do what normally works and, of course, it usually does (Dreyfus, 2004). Nevertheless, their general inability to verbalize their ‘know-how’ (Bjo¨rklund, 2008) means that they hold tacit knowledge (Polanyi, 1966). Experienced teachers are usually able to function automatically. Many of their activities in class, such as their interactions with students, are behavioral patterns that they can invoke and perform without any conscious effort. Experienced teachers seem to have organized their knowledge of students and classrooms in particularly effective patterns that can be retrieved unconsciously from their long-term memory via classroom cues (Johansson & Kroksmark, 2004). The inability to verbalize tacit knowledge, and the fact that teachers may not even know that it is there controlling their decisions and actions, led us to search for a suitable method to elicit teachers’ tacit non-verbal views about the knowledge required for teaching. Such a method was suggested by the American psychologist, George Kelly, who formulated the Personal Construct Psychology theory (Kelly, 1955). Kelly (1955) argued that people have different views of events in the world. These views are organized uniquely within each person’s cognitive structure. Kelly (1955) established a psychological theory, the Personal Construct Psychology, which argues that each person makes use of unique personal criteria—constructs—to help him or her construe meaning from events. The Personal Construct Psychology theory states that people’s views of the objects and events with which they interact are made up of a collection of related similarity–difference dimensions, referred to as personal constructs (Kelly, 1955, 1969). These constructs serve as mental models that enable individuals to formulate testable hypotheses about future events, and then test them against their experience and revise them (Ben-Zvi Assaraf & Damri, 2009; Duit & Glynn, 1996; Duit & Treagust, 2003). Kelly drew explicit parallels between the processes that guide scientific research and those involved in everyday activities (Bezzi, 1996; Bradshaw, Ford, Adams-Webber, & Boose, 1993). Like scientists, people tend to predict and control the course of events in their environment by controlling mental models of the world. Such acts or judgments of events are often experienced as intuition or gut feelings (Jankowicz, 2001) because of their tacit nature. Following the formulation of the Personal Construct Psychology theory, Kelly (1955) designed a method to elicit personal constructs, namely tacit knowledge, which is known as the repertory grid technique (RGT). The RGT has been used in clinical psychology for over 50 years but has recently found new uses in a variety of research areas (Jankowicz, 2004). The findings from experimental psychology and cognitive science on implicit learning and knowledge, and the interest in tacit knowledge, have given rise to new expectations for the use of this method in the area of educational research (Bjo¨rklund, 2008). Tacit cognitive constructs in the area of science education have been previously elicited to probe students’ system-thinking skills
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
(Ben-Zvi Assaraf & Orion, 2005; Keynan, Ben-Zvi Assaraf, & Goldman, 2014), explore the perceptions held by a university geology instructor and his students (Bezzi, 1999), explore possible relationships between teachers’ conceptions about science and the types of inquiry activities in which they engage students (Bencze, Bowen, & Alspo, 2006), and investigate the change in teachers’ reflections on the nature of science when teaching a new syllabus (Henze, Van Driel, & Verloop, 2007b). 2.3. The repertory grid technique (RGT) The RGT is designed to elicit and probe personal tacit views. It is a phenomenological approach which is more closely aligned with grounded theory and interpretive research than with positivist, hypothesis-testing approaches. The focus is on understanding, before developing theories that can be subsequently proved or disproved (Edwards, McDonald, & Young, 2009). The technique appeals to the person’s concurrent tacit views on a given topic and encourages that person to confront his or her intuitions, to make the tacit explicit (Jankowicz, 2001). To further clarify the RGT, here we describe its general principles. The details of the method used in this study are described in the methods section. Every grid of the RGT consists of four components: topic, elements, constructs and rating. These components are usually elicited in a four-step procedure between an interviewer and an interviewee: (1) introducing the topic; (2) eliciting the elements; (3) eliciting the constructs; (4) rating. Elicitation of elements (alternative events, states, or entities within a particular topic) and constructs (dimensions of similarity and differences between elements) is central to knowledge representation in the repertory grids. The RGT allows identifying what a person means when she or he uses elements and constructs, and provides a picture of what a person wishes to say about the topic in question. In recent years, some researchers using repertory grids have deviated from Kelly’s underpinning assumption that each individual constructs his or her world model personally. This has led to the emergence of three types of grids: (i) full repertory grid, where the individual elicits both the elements and constructs; (ii) partial repertory grid, where the individual is supplied with the elements and then identifies his or her personal constructs; (iii) fixed grid, where the individual is supplied with both the elements and the constructs (Edwards et al., 2009). Kelly (1969) assumed that the meaning we attach to events or objects defines our subjective reality, and thus the way in which we interact with our environment. There are no absolutes, no right or wrong answers. The theory is best used when participants have practical experience with the studied domain because they must be able to identify representative elements and compare them through a set of their own criteria (constructs). Researchers choosing to use the repertory grid argue that this technique is free of external influences (Bezzi, 1999; Fransella et al., 2004; Henze et al., 2007b; Jankowicz, 2004; Keynan et al., 2014). The repertory grid overcomes the difficulties inherent in the collection of data with ‘‘traditional’’ instruments of investigation, in which interviewees are supposed to perceive and interpret the researcher’s questions to match the researcher’s meaning. Problems of interpretation also exist in the clarification of observations or questionnaires, because these may force responders into predetermined channels dependent upon cultural assumptions and purposes designed by researchers (Bezzi, 1999). The RGT allows expression of their view by means of their own constructs. The RGT cluster allows the investigator to identify what the other person means when she or he uses the terms suggested as an element and a construct. Each element is rated on each construct to provide a picture of his or her personal mental
21
model—a statement of the way in which the individual thinks of, gives meaning to, and in essence constructs the topic in question (Jankowicz, 2004). As mentioned above, the goals of this study were to expose inservice biology teachers’ views about the knowledge required for teaching biology and their tacit views about the relationships between CK and PCK, using the full RGT. Consequently, this study’s research questions are: (i) What are the participating biology teachers’ views about the knowledge required for teaching biology? (ii) What are the participating teachers’ tacit views about the relationships between CK and PCK? 3. Methodology 3.1. Research context The context of this study is an intense professional development program for in-service high-school science teachers, entitled the ‘‘The Rothschild–Weizmann Program for Excellence in Science Education’’ given at the Weizmann Institute of Science. The aim of this program is to provide a learning environment designed to enrich the participating teachers’ knowledge in both contemporary topics in science or mathematics and science-education theories. The Rothschild–Weizmann Program is specially designed for high-school science teachers who hold a Bachelor of Science (BSc) degree. The participating teachers are studying toward their Master’s degree in science education without a thesis in the course of the program, and are funded by a two-year scholarship. The program’s curriculum runs for eight hours a day, twice a week, over the course of four semesters. Each semester, the teachers participate in different science and science-education courses. The program for biology teachers includes a mandatory longterm ‘‘Designing New Teaching and Learning Materials’’ workshop, which served as the context for this research. The workshop is aimed at promoting the teachers’ professional development through design activities. The workshop lasts three semesters and the products of this longitudinal workshop are the teachers’ final projects of their Master’s studies (Rozenszajn & Yarden, 2014b). The first author of this report is one of the lecturers in the long-term workshop. 3.2. Research population The population of this study consisted of a total of 23 biology teachers participating in the above-described professional development program during the years 2008–2013. The study population included experienced in-service high-school biology teachers with an average 12.6 years of teaching experience at the beginning of the program. The participating teachers taught in a variety of high schools: national (n = 14), religion-oriented (n = 7), boarding school (n = 1), and Bedouin (n = 1). The teachers learned in three different classes during the years 2008–2013: (i) class BI consisted of 4 teachers who studied from 2008 to 2010 (teachers B1–B4); (ii) class BII consisted of 12 teachers who studied from 2009 to 2011 (teachers B5–B16); (iii) class BIII consisted of 7 teachers who studied from 2011 to 2013 (teachers B17–B23). During the ‘‘Designing New Teaching and Learning Materials’’ workshop, the teachers were encouraged to use the new knowledge acquired during the program’s courses in the design of their new teaching and learning materials. The teachers implemented their newly designed materials in their classes, giving them the opportunity to assess the feasibility of the new materials in their everyday practice. The products of this longitudinal workshop were the biology teachers’ final projects of their studies.
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
22
(usually between four and six) in each cluster. Each teacher was then asked to write down the opposite of a given construct, meaning that he or she had to define the construct poles (for an example of construct definitions and their opposites see the right and left columns in Table 1). Then the teacher was handed an empty table (similar to the one presented in Table 1) and asked to write the poles of each construct at opposite ends of each row. On the right-hand side, the teacher was asked to write the definition of each construct and on the left-hand side, the opposite of the construct’s definition. Each teacher was also asked to write his or her 12 elements, each as a header of a separate column. Then each teacher was asked to rate the correlation between each element and each construct on a five-point scale in which ‘1’ means ‘totally agree with the left pole of the construct’ and ‘5’ means ‘totally agree with the right pole of the construct’ (for an example of a full table, see Table 1). The full tables constructed by each teacher were handed to the researcher for computed data analysis. The analysis is described in detail in the cluster analysis section further on.
3.3. Repertory grid technique (RGT) The participating teachers’ views about the knowledge required for teaching biology and their tacit views about the relationships between CK and PCK were exposed using the RGT. Every grid consisted of four components: topic, elements, constructs and rating. We followed the four-step procedure of the full RGT with each group of teachers separately, at the termination of the professional development program. The four steps that were taken are detailed in the following. Step 1—introducing the topic. The topic of this research was teachers’ views about the knowledge required for teaching biology and their tacit views about the relationships between CK and PCK. As such, our interest in teachers’ views was first declared to each group of teachers. We then briefly introduced the main rationale of the Personal Construct Psychology theory (Kelly, 1955, 1969) and the idea that experts hold tacit knowledge (Polanyi, 1966), using a PowerPoint presentation that was specifically designed for this introduction. Included were slides that presented the idea of ‘teachers’ knowledge’ following Shulman’s (1986) theory. Then the notion of experts’ tacit knowledge (Polanyi, 1966) was explained, as well as Kelly’s Personal Construct Psychology theory (1955). At the end of the presentation, which lasted approximately half an hour, it was emphasized that there are no ‘right’ or ‘wrong’ answers and that we are interested in each teacher’s unique views about knowledge for teaching biology. We then asked them to answer the main question of our study: ‘‘What does a biology teacher need to know in order to be a good biology teacher?’’ by eliciting 12 elements of biology teachers’ knowledge (see step 2 below). Each group of participants was separately asked the same question. Step 2—eliciting the elements. From this step on, each teacher filled in the repertory grid individually but teachers from each group stayed in the same room. Each teacher was asked to write down, on 12 separate cards, the elements that a teacher should possess to be a good biology teacher (for an example of elements elicited by one of the teachers, see Table 1). Step 3—eliciting the constructs. The constructs in this research were elicited following Kelly’s method of triads (Kelly, 1955). Each teacher was asked to fold each element card so that he or she could not see what was written on it, place all 12 cards on the table and randomly pick three cards. Then, each teacher was asked to write down the contained elements in a four-column table, each element in a separate column, and to choose the exceptional element of the three, circle it, and write down in the fourth column the reason that two of the elements were similar and the third exceptional. The teachers were then asked to refold the cards, return them to the table, mix them and then again randomly choose three cards. This action was repeated 10 times with each interviewee. Step 4—rating. At this stage each teacher was briefly interviewed individually to define his or her constructs. Repeated explanations for choosing the exceptional elements were defined as constructs, which is why there were only a few constructs
3.4. Content analysis The content analysis of the RGT was used to elicit the participating teachers’ views about the knowledge that is required for teaching biology. For content analysis of the repertory grid data, all of the interviewees’ elements were pooled and categorized according to the meanings they expressed (following, Rozenszajn & Yarden, 2014b). Accordingly, the PCK components included teachers’ knowledge and beliefs about: (i) teaching strategies; (ii) assessment of related contents; (iii) curriculum; (iv) available teaching facilities; (v) students’ meaningful learning; (vi) students’ motivation to learn biology; (vii) the influence of biology learning on students’ future lives; (viii) students’ prior knowledge; (ix) students’ thinking skills; (x) students’ interest outside of the school context. The CK component included science subject matter (Rozenszajn & Yarden, 2014b). The content analysis enabled characterizing the teachers’ repertoire of knowledge elements as a community of high-school biology teaching experts. After categorizing all of the elements, we calculated the number of teachers that mentioned each category of elements to understand which of these categories was considered important for teaching biology for most of study’s population. 3.5. Cluster analysis The cluster analysis was used to elicit teachers’ tacit views about the relationships between CK and PCK. Once the constructs were elicited and rated, the cluster-analysis calculations were performed with REPGRID version 5 software (http://gigi.cpsc. ucalgary.ca:2000/). This program provides a two-way cluster analysis which demonstrates the coherence rate between different elements and the coherence rate between different constructs (Jankowicz, 2004)
Table 1 Teacher B3’s table of elements and constructs, assembled at the end of the repertory grid technique. Constructb
Elementa Ce
Not Not Not Not
a content knowledge an inquiry, practical for teaching a skill a teaching tool
c
5 4 1 1
Constructb
I
Co
M
HB
V
TS
CT
CE
Ex
L
Ec
3 5 5 4
3 4 3 5
4 3 5 5
5 2 2 2
5 2 1 1
4 4 5 3
4 3 5 4
5 5 5 4
4 5 5 4
4 5 5 5
5 4 1 1
Content knowledge Inquiry, practical for teaching A skill A teaching tool
a Element: component that is important for teaching biology. Ce = cell; I = inquiry; Co = computer; M = modeling; HB = the human body; V = volume; TS = transfer skills; CT = critical thinking; CE = a controlled experiment; Ex = experiment; L = laboratory; Ec = ecology. b Construct: dimension of similarity or difference between elements. c The numbers represent the correlation between elements and the related construct; ‘1’ means ‘totally agree with the left pole of the construct’; ‘5’ means ‘totally agree with the right pole of the construct’. A teacher can choose any number between 1 and 5 which expresses the rate of correlation between constructs and elements.
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
Over 80% similarity is considered high coherence between the repertory grid’s elements or constructs (Kelly, 1969). The distance between elements or constructs is considered a ‘safe’ measure for examining the association among elements or constructs (Fransella et al., 2004). The meaning of the high coherence between elements or constructs allowed us to identify cognitive links between elements and between constructs, thus presenting an image of each teacher’s personal mental model—a precise statement of the way in which the teacher thinks of or gives meaning to the topic in question (Jankowicz, 2004). Subsequently, we searched for more than 80% coherence between different elements, and more than 80% coherence between different constructs, thus allowing us to identify the teachers’ tacit knowledge about the relationships between different teachingknowledge categories. Each teacher’s data were analyzed individually. We then analyzed the differences and similarities between all of the clusters’ content-analysis results. 3.6. Validation of the RGT According to Kelly (1969), validity of the RGT is equated with usefulness. Thus many studies are performed using the Personal Construct Psychology theory and the RGT as a way of exploring whether or not the grids are of value for them. Fransella et al. (2004) presented a massive assortment of studies performed since 1977 which found the RGT to be useful in clinical settings, education, language acquisition, forensic work, market research, politics, and organization and business applications. We also performed interviews for interpretive validity with five biology teachers. During the interviews, the teachers were asked to express their views about the relationships between some of the elements that showed high coherence (more than 80%). All five teachers easily provided explanations for the relationships between the elements. Their explanations were aligned with the RGT results. Furthermore, the grid maps and our analysis were presented to the teachers, and they were asked to express their views on the accuracy of the results and their views about the value of acquiring biological content knowledge for teaching practice. The teachers agreed completely with our analysis and even expressed their surprise at the accuracy of the results. The overall validation rate was 100%. That is, all of the teachers explained the connections between the elements that were grouped by the RGT and explained the separation between different elements that showed less than 80% coherence in a way that was aligned with our analysis. 4. Results 4.1. Content analysis—teachers’ views about the knowledge required for teaching biology Initially, we examined the participating teachers’ views about the knowledge required for teaching biology using the knowledge elements that the in-service biology teachers viewed as important for teaching biology. Each teacher elicited between 9 and 12 elements, and altogether the 23 teachers elicited 260 elements. The 260 elements included 194 different elements, i.e., 75% of the elements were mentioned only by one teacher and 66 of the elements (25%) were mentioned by 2–12 different teachers. Thus, the teachers who participated in this study possessed a diverse repertoire of knowledge elements required for teaching. The elements were categorized according to their content (following, Rozenszajn & Yarden, 2014b). Six main groups of elements emerged in the course of the content analysis: (i) subject matter CK, namely knowledge of science contents (Rozenszajn & Yarden, 2014b), such as: ‘biological knowledge’, ‘knowledge about levels of organization’ and ‘deep knowledge in science’; (ii)
23
teaching strategies, namely knowledge about the ways a teacher should teach (Rozenszajn & Yarden, 2014b), such as: ‘clear explanations’, ‘the ability to simplify complex processes’, and ‘asking questions while teaching’; (iii) teacher’s personality, namely personal characteristics of the teacher that may influence teaching, such as: ‘creativity’, ‘moral personality’, and ‘loves people’; (iv) meaningful learning, namely knowledge about the factors that influence meaningful learning (Rozenszajn & Yarden, 2014b), such as: ‘students’ misconceptions’, ‘difficulties in comprehending a specific idea’, and ‘motivation to learn science’; (v) relevance, namely knowledge about the connection between contents taught in class and the students’ everyday lives, such as: ‘updated in the students’ world and respects it’, and ‘uses concepts of the students’ everyday life’, and (vi) learner’s personality, namely knowledge about the personal characteristics of students that may influence learning, such as: ‘student’s curiosity’, ‘student’s personality’. Examining the frequency of the elicited elements revealed the CK category as the most frequently mentioned one (33% of all of the elements). Namely, one out of every three elements that were elicited by the teachers was a CK element. Interestingly, elements from the CK category were mentioned by all of the teachers, whereas elements from the other categories were mentioned only by several teachers. The second most frequently mentioned category was teacher’s personality (29%), followed by teaching strategies (25%) and then meaningful learning (10%), relevance (2%) and learner’s personality (1%). 4.2. Cluster analysis—relationships between CK and PCK To better understand the significance of the elicited elements to the high-school biology teachers, each teacher was asked to select an exceptional element among three randomly selected ones, explain her or his selection and repeat this step 10 times. Constructs were then defined based on the teacher’s repeated explanations of the exceptional element. Then, each teacher was asked to fill out a table with ratings of each element relative to each construct (similar to Table 1). The computed outcome of the ratings given by each teacher was a two-dimensional tree diagram—a cluster—which represents similarities between rating patterns of the elements elicited by each teacher (Figs. 1 and 2). We then looked at each teacher’s cluster and searched for high coherence (more than 80%) between elements. All 23 teachers’ clusters showed high coherence between different CK elements (more than 80%) but within most of the teachers’ clusters (74%), high coherence was not found between elements of the CK category and other elements’ categories (for example see Fig. 1). Namely, the other CK elements appeared to be a separate group of elements among most of the participating teachers’ clusters. High coherence was only identified between elements from the CK category and elements from the other categories in 6 of the 23 teachers’ clusters (26%). Five of these clusters (22% of all clusters) showed high coherence between CK elements and teaching-strategy elements. Two of these clusters (9% of all clusters) showed high coherence between CK elements and teacher’s personality elements. In their interviews, the teachers were asked to explain the value of acquiring biological content knowledge for their teaching practice. They all explained that knowing more biological content helps them understand biology more deeply and therefore enables them to answer their students’ questions more precisely. For example, one of the teachers said in her interview: ‘‘It is very important for teachers to learn updated biological contents because that way I can answer more students’ questions during the lessons and it makes me more confident in the accuracy of my
24
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
Fig. 1. Teacher B3’s repertory grid tree diagram. (1) The 12 elements that were elicited by the teacher. (2) The coherence scale between the elements and its use in defining the coherence rate between the elements. (3) A group of elements with more than 80% coherence. (4) The four constructs that were defined during step 3 of the teacher’s repertory grid. (5) The coherence scale between the constructs and its use in defining the coherence rate between the constructs.
knowledge.’’ That is, their explanations of the value of CK referred only to the growth of their CK and ignored any relation to PCK. These results suggest that most teachers view CK as important but separate from PCK. It is worth noting that one of these clusters, that of Teacher B2, showed high coherence between CK elements and both teaching strategies and teacher’s personality elements (Fig. 2). Teacher B2 was unique in that the analysis of her RGT diagram revealed that she elicited 6 CK elements (of the 12 requested) and her diagram demonstrated high coherence between two of these CK elements: ‘knowledge update’ and ‘knowledge beyond the curriculum’, a PCK
element from the meaningful learning category: ‘scientific literacy’, and four elements from the teacher’s personality category: ‘creativity’, ‘enthusiasm for the wonders of nature’, ‘curiosity’, and ‘openness to new ideas and questions’ (Fig. 2). The interview used to validate the results of her cluster revealed that Teacher B2 views acquisition of biological CK as a very important factor in her professional development, and as very important for her teaching and for her students’ learning. In the interview, she kept saying that she believes that: ‘‘knowledge is power,’’ namely that acquiring CK in biology empowers her and enables her to teach better.
Fig. 2. Teacher B2’s repertory grid tree diagram. (1) The 12 elements that were elicited by the teacher. (2) The coherence scale between the elements and its use in defining the coherence rate between the elements. (3) An example of the two groups of elements relating to CK with more than 80% coherence. (4) The constructs that were defined during step 3 of the teacher’s repertory grid. (5) The coherence scale between the constructs, and (6) its use in defining more than 90% coherence between CK and other constructs by drawing a line between the constructs that are in the same group with the CK construct (‘a thinking skill’; ‘content knowledge’; ‘a subject of the teachers’ toolbox’) toward the constructs’ coherence-rate scale.
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
A similar analysis was performed for the constructs elicited by the teachers. The analyses of the RGT data collected from each of the 23 teachers revealed that 17 of them (74%) elicited the CK construct during step 3 of the RGT. Six teachers did not elicit the CK construct at all. In 15 out of 17 clusters that included CK constructs, CK appeared as a separate construct with a low coherence rate (less than 80%) to the other constructs (for example see Fig. 1). Only two teachers’ clusters, Teacher B2 and Teacher B21, showed high coherence between the construct ‘content knowledge’ and the others. Teacher B2’s cluster showed high coherence (over 90%) between the CK construct: ‘content knowledge’ and the PCK constructs: ‘a subject of the teacher’s toolbox’ and ‘a thinking skill’. These constructs were categorized as PCK constructs following the interview with Teacher B2. That is, Teacher B2’s cluster demonstrated high coherence (more than 80%) between the CK and PCK constructs (Fig. 2). Teacher B21’s cluster demonstrated high coherence (more than 80%) between the CK construct and the construct ‘professional development’ (data not shown). She is the only teacher who teaches both biology and biotechnology in high school. Taken together, the analyses of the elements and of the constructs elicited by each of the participating teachers suggest that by and large, CK is viewed by most teachers as a distinct category of biology knowledge that is required for teaching biology. 5. Discussion 5.1. Biology teachers’ views about knowledge required for teaching A group of 23 high-school biology teachers were asked to intuitively elicit knowledge elements that they view as important for teaching biology. The teachers elicited a diverse repertoire of knowledge elements which were categorized into six knowledge categories. The only category that was mentioned by all of the teachers as an important biology teaching element was CK. Intuitive elicitation of elements is important, because the elements come from the interviewee’s cognitive structure with minimal impact from the researcher (Bezzi, 1999; Fransella et al., 2004; Henze et al., 2007b; Jankowicz, 2004). The elements that were intuitively elicited in the course of this research raise three major issues: (i) views about knowledge for teaching are personal (following Kelly, 1955). Appealing to the biology teachers’ views, we found that 75% of the elements that they elicited were unique. Each teacher who participated in this research probably holds unique views about the knowledge elements required for teaching, and these elements are uniquely distributed among the element categories in each teacher’s cognitive structure. This emphasizes the importance of considering diverse teaching perspectives when planning professional development programs (Rozenszajn & Yarden, 2011, 2014b); (ii) views about knowledge are socially distributed (following Collins, Brown, & Newman, 1989). Pooling all of the elements elicited by the various teachers demonstrated the variety and large scope of the teachers’ views about knowledge within the area of biology teaching, thus emphasizing the importance of sharing among teachers during professional development programs; (iii) CK is an important knowledge component for biology teachers’ practice. Of all of the elements that were elicited by the teachers, CK was the only element that all teachers mentioned. In addition, our analysis revealed that the CK category of elements was the most variable category of elements that was most frequently mentioned by the teachers. Although the cognitive structure of the teachers is variable, the relatively high frequency of elicitation of CK elements within all of the teachers’ data suggests that CK is viewed as an important factor for these teachers’ knowledge for practice
25
(following Fernandez-Balboa & Stiehl, 1995; Marks, 1990), yet it differs from other PCK components. 5.2. Biology teachers’ tacit views about the relationships between CK and PCK Investigating the interrelationships between the various knowledge components elicited by each teacher as knowledge elements that are important for teaching biology may shed light on the nature of PCK and its role in teachers’ practice (Abell, 2008; Friedrichsen, Van Driel, & Abell, 2011; Park & Chen, 2012). Park and Chen (2012), who examined the declarative dimensions of PCK, showed that biology teachers tend to connect knowledge of students’ understanding and knowledge of instructional strategies and representation, and that these two PCK components might be a target area for PCK improvement. Here we examined the possible tacit views of teachers on the relationships between CK and PCK by means of a full RGT, and showed that biology teachers refer to CK as an important construct, yet different from PCK. The RGT is aimed at eliciting experts’ tacit personal views. Examining teachers’ views about the knowledge required for teaching using a technique that minimizes the researcher’s own interpretation and impact enabled us to reveal tacit dimensions of teachers’ views about the knowledge required for teaching. The fact that all of the teachers chose to elicit CK elements and 74% of the teachers sorted the elements using a ‘CK’ construct reinforces the idea that CK is viewed as an important factor in biology teachers’ practice. But is CK an integral part of teachers’ PCK or is it an independent knowledge type? This question has been much discussed in the literature (Childs & McNicholl, 2007; FernandezBalboa & Stiehl, 1995; Grossman, 1990; Kleickmann et al., 2013; Krauss et al., 2008; Lederman & Gess-Newsome, 1992; Loughran et al., 2008; Magnusson et al., 1999; Marks, 1990; Shulman, 1987). Our findings indicate that CK may not be an integral part of biology teachers’ PCK, as suggested by Lee and Luft (2008) and others (Ball et al., 2008; Hill, 2008), but can be considered a separate entity, as suggested by Shulman (1986, 1987). Nevertheless, further examination of these interrelationships is still needed. Although our analysis of the repertory grid data revealed that most biology teachers view CK as a different component of knowledge, distinct from PCK, six teachers’ clusters demonstrated high coherence between CK elements and elements that describe teaching strategies. This suggests that although CK forms a different knowledge group, there are teachers who consider CK an important part of their PCK. Therefore, these teachers hold a view of knowledge in which content and pedagogy are integrated (Gess-Newsome, 1999; Krauss et al., 2008). It is possible that these teachers did integrate their CK with their PCK after taking academic biology and science-education courses during the professional development program (Krauss et al., 2008), while the other teachers did not assimilate new CK into their existing PCK. One possible explanation for the teachers not integrating CK with PCK may lie in the fact that some teachers need to be encouraged to assimilate new CK into their existing PCK. Another possible explanation may be that different teachers hold different teaching perspectives. Some teachers view teaching and learning biology as a field that should be mainly based on subject matter CK, while others view teaching and learning biology as dependent on cognitive processes, such as encouraging high-order thinking skills (Rozenszajn & Yarden, 2011, 2014a). It is possible that we did not reveal additional tacit views about knowledge for teaching while using the RGT. However, it is worth noting that all except one of the participating teachers chose not to insert new CK acquired in the professional development program into the learning materials they designed in the course of the program. The only teacher who
26
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27
did insert newly acquired CK into the learning materials she designed was Teacher B2 who, during the RGT, elicited numerous CK elements. She was the only teacher whose cluster showed high coherence between CK and PCK elements and high coherence between CK and PCK constructs. The question of why some teachers distinguish between CK and PCK while others do not remains open, and is a subject for further research. The analysis of CK constructs reinforced the conclusions of the analysis of CK elements. Teachers make sense of their practice through constructs regarding teaching. Constructs are frequently expressions of intuition, ‘‘gut feelings’’ that the individual uses as a guide to action (Bjo¨rklund, 2008). Seventy-four percent of the teachers who participated in this research used the CK constructs as an integral part of their cognitive structure about the knowledge required for teaching biology, but the coherence rate between CK constructs and other constructs within most clusters was low. That is, CK is viewed as an important but separate domain of knowledge for teaching in most of these teachers’ cognitive structures. Only two teachers’ clusters—those of Teacher B2 and Teacher B21— showed high coherence between CK constructs and others. As already noted, Teacher B2 viewed acquisition of biological CK as a very important factor in her professional development and a very important factor of her teaching and her students’ learning. As the only teacher who teaches both biology and biotechnology—two contemporary topics—in high school, it can be assumed that Teacher B21 needs to acquire advanced biological content for her professional development. We realize that although our results may imply that by and large, the participating teachers tend to distinguish CK from PCK, the RGT might have failed to reveal some hidden links in the teachers’ views. Therefore, further research which will employ other methods and possibly a bigger teacher population with different professional development opportunity contexts should be conducted to answer the currently raised question; results might subsequently be useful in designing effective professional development programs. This research suggests that CK is a separate domain within the participating biology teachers’ views regarding the knowledge required for teaching biology. The theoretical framework related to PCK usually excludes CK (Grossman, 1990; Magnusson et al., 1999; Shulman, 1987; Tamir, 1988). However, some practical studies of PCK within educational systems emphasize the importance of CK and include it as an integral construct of PCK (Fernandez-Balboa & Stiehl, 1995; Marks, 1990). This study strengthens the notion that teachers view CK as important, but a distinct domain of knowledge for biology teachers’ practice. Understanding biology teachers’ views about the knowledge required for teaching might be an important factor in professional development programs aimed at enhancing teachers’ professionalism (Henze, Van Driel, & Verloop, 2007a; Loughran, Berry, & Mulhall, 2012). We suggest that biology teachers’ professional development programs include updated biological knowledge courses, since such knowledge is viewed as a very important factor in biology teachers’ professionalism. However, designers of professional development programs should take into account that updated biological knowledge courses may empower biology teachers and enrich their CK, but it may have little influence on their PCK. It is likely that even if teachers do link CK and PCK to some extent in their practice, it is important to look for means that might promote the ability to recognize this link and articulate it during professional development programs. Since it has been shown that designing new teaching activities promotes teachers’ PCK (Rozenszajn & Yarden, 2014a), we recommend adding a workshop to each biological knowledge course, in which teachers will be encouraged to design new teaching activities that connect the content of the course to class. Further research may evaluate
whether this kind of workshop promotes interconnections between CK and the developing PCK. Acknowledgements We thank the teachers who participated in this study for their cooperation, and Orit Ben-Zvi Assaraf for reviewing an earlier version of this manuscript. This research was supported by the Israel Science Foundation (grant No. 836/09). References Abell, S. K. (2008). Twenty years later: Does pedagogical content knowledge remain a useful idea? International Journal of Science Education, 30(10), 1405–1416. Ball, D. L., Thames, M. H., & Phelps, G. (2008). Content knowledge for teaching what makes it special? Journal of Teacher Education, 59(5), 389–407. Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., et al. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180. Ben-Zvi Assaraf, O., & Damri, S. (2009). University science graduates’ environmental perceptions regarding industry. Journal of Science Education and Technology, 18(5), 367–381. Ben-Zvi Assaraf, O., & Orion, N. (2005). Development of system thinking skills in the context of earth system education. Journal of Research in Science Teaching, 42(5), 518–560. Bencze, J. L., Bowen, G. M., & Alspo, S. (2006). Teachers’ tendencies to promote student-led science projects: associations with their views about science. Science Education, 90(3), 400–419. Bezzi, A. (1996). Use of repertory grids in facilitating knowledge construction and reconstruction in geology. Journal of Research in Science Teaching, 33(2), 179– 204. Bezzi, A. (1999). What is this thing called geoscience? Epistemological dimensions elicited with the repertory grid and their implications for scientific literacy. Science Education, 83(6), 675–700. Bjo¨rklund, L. (2008). The repertory grid technique: Making tacit knowledge explicit: assessing creative work and problem solving skills. In H. Middleton (Ed.), Researching technology education: Methods and techniques (pp. 46–69). Rotterdam, The Netherlands: Sense. Bradshaw, J. M., Ford, K. M., Adams-Webber, J. R., & Boose, J. H. (1993). Beyond the repertory grid: New approaches to constructivist knowledge-acquisition tool development. In K. M. Ford & J. M. Bradshaw (Eds.), Knowledge acquisition as modeling (pp. 287–333). New York, NY: Wiley. Chi, M. T. H. (2006). Two approaches to the study of experts’ characteristics. In K. A. Ericsson (Ed.), The Cambridge handbook of expertise and expert performance (pp. 21–38). New York, NY: Cambridge University Press. Childs, A., & McNicholl, J. (2007). Investigating the relationship between subject content knowledge and pedagogical practice through the analysis of classroom discourse. International Journal of Science Education, 29(13), 1629–1653. Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing and mathematics. New York, NY: L Erlbaum. De Jong, O., & Van Der Valk, A. E. (2007). Science teachers’ PCK and teaching practice: Learning to scaffold students’ open-inquiry learning. In R. Pinto & D. Couso (Eds.), Contributions from science education research (pp. 107–118). Dordrecht, The Netherlands: Springer. Dreyfus, S. E. (2004). The five-stage model of adult skill acquisition. Bulletin of Science, Technology & Society, 24(3), 177–181. Duit, R., & Glynn, S. M. (1996). Mental modeling. London, UK: Falmer Press. Duit, R., & Treagust, D. F. (2003). Conceptual change: A powerful framework for improving science teaching and learning. International Journal of Science Education, 25(6), 671–688. Edwards, H. M., McDonald, S., & Young, S. M. (2009). The repertory grid technique: Its place in empirical software engineering research. Information and Software Technology, 51(4), 785–798. Even, R. (2011). The relevance of advanced mathematics studies to expertise in secondary school mathematics teaching: practitioners’ views. The International Journal of Mathematics Education, 43(6), 941–950. Fernandez-Balboa, J., & Stiehl, J. (1995). The generic nature of pedagogical content knowledge among college professors. Teaching and Teacher Education, 11(3), 293–306. Fransella, F., Bell, R., & Bannister, D. (2004). A manual for repertory grid technique.. Chichester, England: Wiley. Friedrichsen, P. J., Van Driel, J. H., & Abell, S. K. (2011). Taking a closer look at science teaching orientations. Science Education, 95(2), 358–376. Gess-Newsome, J. (1999). Pedagogical content knowledge: An introduction and orientation. In J. Gess-Newsome & N. G. Lederman (Eds.), Examining pedagogical content knowledge: PCK and science education (pp. 3–17). Dordrecht, The Netherlands: Kluwer. Grossman, P. L. (1990). The making of a teacher: Teacher knowledge and teacher education. New York, NY: Teachers College Press. Großschedla, J., Mahlera, D., Kleickmann, T., & Harmsa, U. (2014). Content-related knowledge of biology teachers from secondary schools: Structure and learning opportunities. International Journal of Science Education, 36(14), 2335–2366.
R. Rozenszajn, A. Yarden / Studies in Educational Evaluation 47 (2015) 19–27 Henze, I., Van Driel, J. H., & Verloop, N. (2007a). The change of science teachers’ personal knowledge about teaching models and modeling in the context of science education reform. International Journal of Science Education, 29(15), 1819–1846. Henze, I., Van Driel, J. H., & Verloop, N. (2007b). Science teachers’ knowledge about teaching models and modeling in the context of a new syllabus on public understanding of science. Research in Science Education, 37(2), 99–122. Henze, I., Van Driel, J. H., & Verloop, N. (2008). Development of experienced science teachers’ pedagogical content knowledge of models of the solar system and the universe. International Journal of Science Education, 30(10), 1321–1342. Hill, H. C. (2008). Unpacking pedagogical content knowledge: Conceptualizing and measuring teachers’ topic-specific knowledge of students. Journal of Research in Mathematics Education, 39(4), 372–400. Jankowicz, D. (2001). Why does subjectivity make us nervous? Making the tacit explicit. Journal of Intellectual Capital, 2(1), 61–73. Jankowicz, D. (2004). The easy guide to repertory grids. Chichester, UK: Wiley. Johansson, T., & Kroksmark, T. (2004). Teachers’ intuition-in-action: How teachers experience action. Reflective Practice, 5(3), 357–381. Ka¨pyla¨, M., Heikkinen, J. P., & Asunta, T. (2009). Influence of content knowledge on pedagogical content knowledge: The case of teaching photosynthesis and plant growth. International Journal of Science Education, 31(10), 1395–1415. http:// dx.doi.org/10.1080/09500690802082168 Kelly, G. A. (1955). The psychology of personal constructs (Vol. 1). New York, NY: Norton and Co. Kelly, G. A. (1969). Personal construct theory and the psychotherapeutic interview. In B. Maher (Ed.), Clinical psychology and personality: The selected papers of George Kelly (pp. 224–232). New York, NY: Wiley. Keynan, A., Ben-Zvi Assaraf, O., & Goldman, D. (2014). The repertory grid as a tool for evaluating the development of students’ ecological system thinking abilities. Studies in Educational Evaluation, 41, 90–105. Kleickmann, T., Richter, D., Kunter, M., Elsner, J., Besser, M., Krauss, S., et al. (2013). Teachers’ content knowledge and pedagogical content knowledge: The Role Of structural differences in teacher education. Journal of Teacher Education, 64(1), 90–106. Krauss, S., Brunner, M., Kunter, M., Baumert, J., Blum, W., Neubrand, M., et al. (2008). Pedagogical content knowledge and content knowledge of secondary mathematics teachers. Journal of Educational Psychology, 100(3), 716–725. Lederman, N. G., & Gess-Newsome, J. (1992). Do subject matter knowledge, pedagogical knowledge, and pedagogical content knowledge constitute the ideal gas law of science teaching? Journal of Teacher Education, 3(1), 16–20. Lee, E., & Luft, J. A. (2008). Experienced secondary science teachers’ representation of pedagogical content knowledge. International Journal of Science Education, 30(10), 1343–1363. Loughran, J., Berry, A., & Mulhall, P. (2012). Understanding and developing science teachers’ pedagogical content knowledge (Vol. 2). Clayton: Australia Sense Publishers.
27
Loughran, J., Milroy, P., Berry, A., Gunstone, R., & Mulhall, P. (2001). Documenting science teachers’ pedagogical content knowledge through PaP-eRs. Research in Science Education, 31(2), 289–307. Loughran, J., Mulhall, P., & Berry, A. (2008). Exploring pedagogical content knowledge in science teacher education. International Journal of Science Education, 30(10), 1301–1320. Magnusson, S., Krajcik, J., & Borko, H. (1999). Nature, sources and development of pedagogical content knowledge for science teaching. In J. Gess-Newsome & N. G. Lederman (Eds.), Examining pedagogical content knowledge: PCK and science education (pp. 95–132). Dordrecht, The Netherlands: Kluwer Academic Publishers. Marks, R. (1990). Pedagogical content knowledge: From a mathematical case to a modified conception. Journal of Teacher Education, 41(3), 3–11. Park, S., & Chen, Y. (2012). Mapping out the Integration of the components of pedagogical content knowledge (PCK): Examples from high school biology classrooms. Journal of Research in Science Teaching, 49(7), 922–941. Park, S., & Oliver, J. S. (2008). Revisiting the conceptualization of pedagogical content knowledge (PCK): PCK as a conceptual tool to understand teachers and professionals. Research in Science Education, 38(3), 261–284. Polanyi, M. (1966). The tacit dimension. Gloucester, MA: Doubleday and Co. Rozenszajn, R., & Yarden, A. (2011). Conceptualization of in-service biology teachers’ pedagogical content knowledge (PCK) during a long term professional development program. In A. Yarden & G. S. Carvalho (Eds.), Authenticity in biology education: Benefits and challenges. A selection of papers presented at the 8th conference of European researchers in didactics of biology (pp. 79–90). Rozenszajn, R., & Yarden, A. (2014a). Expansion of biology teachers’ pedagogical content knowledge (PCK) during a long-term professional development program. Research in Science Education, 44(1), 189–213. http://dx.doi.org/ 10.1007/s11165-013-9378-6 Rozenszajn, R., & Yarden, A. (2014b). Mathematics and biology teachers’ tacit views of the knowledge required for teaching: Varying relationships between CK and PCK. International Journal of STEM Education, 1(11) http://dx.doi.org/10.1186/ s40594-014-0011-7 Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14. Shulman, L. S. (1987). Knowledge and teaching: Foundation of the new reform. Harvard Educational Review, 57(1), 1–22. Tamir, P. (1988). Subject matter and related pedagogical content knowledge in teacher education. Teaching and Teacher Education, 4(2), 99–110. Van Driel, J. H., Verloop, N., & De Vos, W. (1998). Developing science teachers’ pedagogical content knowledge. Journal of Research in Science Teaching, 35(6), 673–695. Zeidler, D. L. (2002). Dancing with maggots and saints: Visions for subject matter knowledge, pedagogical knowledge and pedagogical content knowledge in science teacher education reform. Journal of Science Teacher Education, 13(1), 27–42.